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| 비교 탐색적 양적 연구× | 조사 연구× | |
|---|---|---|
| 분야 | 연구설계 | 연구설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | Mid-to-late 20th century | Late 19th century; methodologically systematised 1940s–1960s |
| 창시자≠ | No single originator; codified in quantitative research methodology traditions (20th century) | Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s |
| 유형≠ | Quantitative research design | Quantitative (and mixed) non-experimental design |
| 원전≠ | Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage Publications. ISBN: 978-1452226101 | Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000 |
| 별칭 | exploratory comparative quantitative design, comparative exploratory survey research, quantitative comparative exploration, CEQR design | survey methodology, questionnaire research, survey design, survey study |
| 관련≠ | 3 | 4 |
| 요약≠ | Comparative exploratory quantitative research is a design that uses structured numerical data collection to discover patterns, differences, and relationships across two or more distinct groups or conditions — without a fully specified hypothesis in advance. It sits at the intersection of exploratory intent and comparative structure: the researcher does not enter the field with a predetermined answer but organises the inquiry around a comparison that will generate quantitative insights. The design is common in social, educational, and behavioural sciences when a phenomenon is insufficiently understood to permit confirmatory testing but structured group comparison is still feasible and informative. | Survey research is a quantitative (and sometimes mixed-methods) design in which a researcher collects standardised self-report data from a sample drawn from a defined population, using a questionnaire or structured interview. It is the dominant non-experimental strategy for describing population characteristics, estimating prevalence, mapping attitude distributions, and testing bivariate or multivariate associations across social, behavioural, and health sciences. |
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